{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import json\n",
    "import keras\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import os\n",
    "import sklearn\n",
    "import sklearn.metrics as skm\n",
    "import sys\n",
    "sys.path.append(\"../../../ecg\")\n",
    "\n",
    "import load\n",
    "import util\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 328/328 [00:00<00:00, 2008.00it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "328/328 [==============================] - 4s 12ms/step\n"
     ]
    }
   ],
   "source": [
    "model_path = \"/deep/group/awni/ecg_models/default/1527627404-9/0.341-0.881-013-0.241-0.911.hdf5\"\n",
    "data_json = \"../test.json\"\n",
    "\n",
    "preproc = util.load(os.path.dirname(model_path))\n",
    "dataset = load.load_dataset(data_json)\n",
    "ecgs, committee_labels = preproc.process(*dataset)\n",
    "\n",
    "with open(data_json, 'r') as fid:\n",
    "    committee_ids = [json.loads(l)['reviewer'] for l in fid]\n",
    "\n",
    "revs = []\n",
    "rev_ids = []\n",
    "for i in range(6):\n",
    "    with open(\"../test_rev{}.json\".format(i), 'r') as fid:\n",
    "        rev_info = [json.loads(l) for l in fid]\n",
    "        revs.append([r['labels'] for r in rev_info])\n",
    "        rev_ids.append([r['reviewer'] for r in rev_info])\n",
    "        \n",
    "revs = [preproc.process_y(r) for r in revs]\n",
    "\n",
    "model = keras.models.load_model(model_path)\n",
    "probs = model.predict(ecgs, verbose=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#ame_ids = [i for i, c in enumerate(committee_ids) if c == [1,2,3]]\n",
    "#ame_revs = [r[same_ids,...] for r in revs]\n",
    "#same_grp = committee_labels[same_ids, ...]\n",
    "#same_probs = probs[same_ids, ...]\n",
    "\n",
    "same_revs = []\n",
    "for rid in range(1, 10):\n",
    "    ids = []\n",
    "    r_labels = []\n",
    "    for rev_id, rev in zip(rev_ids, revs):\n",
    "        rids = [e for e, i in enumerate(rev_id) if i == rid]\n",
    "        ids.extend(rids)\n",
    "        r_labels.append(rev[rids, ...])\n",
    "    same_revs.append((ids, r_labels))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def to_set(preds):\n",
    "    idxs = np.argmax(preds, axis=2)\n",
    "    return [list(set(r)) for r in idxs]\n",
    "\n",
    "def set_stats(ground_truth, preds):\n",
    "    labels = range(ground_truth.shape[2])\n",
    "    ground_truth = to_set(ground_truth)\n",
    "    preds = to_set(preds)\n",
    "    stat_dict = {}\n",
    "    for x in labels:\n",
    "        tp = 0; fp = 0; fn = 0; tn = 0;\n",
    "        for g, p in zip(ground_truth, preds):\n",
    "            if x in g and x in p: # tp\n",
    "                tp += 1\n",
    "            if x not in g and x in p: # fp\n",
    "                fp += 1\n",
    "            if x in g and x not in p:\n",
    "                fn += 1\n",
    "            if x not in g and x not in p:\n",
    "                tn += 1\n",
    "        stat_dict[x] = (tp, fp, fn, tn)\n",
    "    return stat_dict\n",
    "\n",
    "def stats(ground_truth, preds):\n",
    "    labels = range(ground_truth.shape[2])\n",
    "    g = np.argmax(ground_truth, axis=2).ravel()\n",
    "    p = np.argmax(preds, axis=2).ravel()\n",
    "    stat_dict = {}\n",
    "    for i in labels:\n",
    "        # compute all the stats for each label\n",
    "        tp = np.sum(g[g==i] == p[g==i])\n",
    "        fp = np.sum(g[p==i] != p[p==i])\n",
    "        fn = np.sum(g==i) - tp\n",
    "        tn = np.sum(g!=i) - fp\n",
    "        stat_dict[i] = (tp, fp, fn, tn)\n",
    "    return stat_dict\n",
    "\n",
    "\n",
    "stat_dicts = [stats(committee_labels[i,...], np.vstack(r)) for i, r in same_revs]\n",
    "res_dict = {}\n",
    "for k, v in stat_dicts[0].items():\n",
    "    precisions = []\n",
    "    recalls = []\n",
    "    specificities = []\n",
    "    for s in stat_dicts:\n",
    "        tp, fp, fn, tn = s[k]\n",
    "        precisions.append(tp / float(tp + fp))\n",
    "        recalls.append(tp / float(tp + fn))\n",
    "        specificities.append(tn / float(tn + fp))\n",
    "    res_dict[preproc.int_to_class[k]] = {\n",
    "         'precision' : precisions,\n",
    "         'recall' : recalls,\n",
    "         'specificity' : specificities}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def precision_recall_curve(ground_truth, human_res, probs, classes):\n",
    "    gt = np.argmax(ground_truth, axis=2)\n",
    "    if len(classes) == 3:\n",
    "        f, ax = plt.subplots(1,3,figsize=(14,4))\n",
    "    else:\n",
    "        f, ax = plt.subplots(4,3,figsize=(14, 22))\n",
    "        ax = [a for i in ax for a in i]\n",
    "    for e, c in enumerate(classes):\n",
    "        class_idx = preproc.class_to_int[c]\n",
    "        \n",
    "        binary_gt = gt == class_idx\n",
    "        binary_probs = probs[..., class_idx]\n",
    "        ppvs, senss, _ = skm.precision_recall_curve(binary_gt.ravel(), binary_probs.ravel())\n",
    "        h_ppv, h_sens = human_res[c]['precision'], human_res[c]['recall']\n",
    "        h_ppv, h_sens = np.array(h_ppv), np.array(h_sens)\n",
    "        avg_sens, avg_ppv = np.mean(h_sens), np.mean(h_ppv)\n",
    "\n",
    "        cax = ax[e]\n",
    "        cax.plot(senss, ppvs, lw=2, label=\"Model\")\n",
    "        cax.plot(h_sens, h_ppv, 'r+', markersize=10, label=\"Individual Cardiologists\")\n",
    "        cax.plot(avg_sens, avg_ppv, 'go', markersize=6, label=\"Average Cardiologist\")\n",
    "        cax.set_xlim(0.0, 1.01)\n",
    "        cax.set_ylim(0.0, 1.01)\n",
    "        cax.set_title(\"Class {}\".format(c))\n",
    "        cax.set_xlabel('Sensitivity (Recall)')\n",
    "        cax.set_ylabel('PPV (Precision)')\n",
    "        cax.legend(loc=0)\n",
    "\n",
    "    plt.savefig(\"human_model_prec_recall_curve.pdf\",\n",
    "       dpi=400,\n",
    "       format='pdf',\n",
    "       bbox_inches='tight')\n",
    "\n",
    "def roc_curve(ground_truth, human_res, probs, classes,\n",
    "              y_start, file_name):\n",
    "    gt = np.argmax(ground_truth, axis=2)\n",
    "    if len(classes) == 3:\n",
    "        f, ax = plt.subplots(1,3,figsize=(14,4))\n",
    "    else:\n",
    "        f, ax = plt.subplots(4,3,figsize=(14, 22))\n",
    "        ax = [a for i in ax for a in i]\n",
    "    \n",
    "    for e, c in enumerate(classes):\n",
    "        class_idx = preproc.class_to_int[c]\n",
    "        binary_gt = gt == class_idx\n",
    "        binary_probs = probs[..., class_idx]\n",
    "\n",
    "        fps, tps, _ = skm.roc_curve(binary_gt.ravel(), binary_probs.ravel())\n",
    "        h_fps, h_tps = human_res[c]['specificity'], human_res[c]['recall']\n",
    "        h_fps, h_tps = 1 - np.array(h_fps), np.array(h_tps)\n",
    "        avg_fps, avg_tps = np.mean(h_fps), np.mean(h_tps)\n",
    "        cax = ax[e]\n",
    "        cax.plot(fps, tps, lw=2, label=\"Model\")\n",
    "        cax.plot(h_fps, h_tps, 'r+', markersize=10, label=\"Individual Cardiologists\")\n",
    "        cax.plot(avg_fps, avg_tps, 'go', markersize=6, label=\"Average Cardiologist\")\n",
    "        cax.set_xlim(-0.008, 0.5)\n",
    "        cax.set_ylim(y_start, 1.05)\n",
    "        cax.set_title(\"Class {}\".format(c))\n",
    "        cax.set_xlabel('1 - Specificity')\n",
    "        cax.set_ylabel('Sensitivity')\n",
    "        cax.legend(loc=4)\n",
    "\n",
    "    plt.savefig(file_name,\n",
    "       dpi=400,\n",
    "       format='pdf',\n",
    "       bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x288 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "precision_recall_curve(committee_labels, res_dict, probs,\n",
    "                       classes=[\"AF\", \"TRIGEMINY\", \"AVB\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x288 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "roc_curve(committee_labels, res_dict, probs,\n",
    "          classes=[\"AF\", \"TRIGEMINY\", \"AVB\"],\n",
    "          y_start=0.3,\n",
    "          file_name=\"human_model_roc.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x1584 with 12 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "roc_curve(committee_labels, res_dict, probs,\n",
    "          classes=preproc.classes,\n",
    "          y_start=0.0,\n",
    "          file_name=\"human_model_roc_all.pdf\")"
   ]
  }
 ],
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